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Analyses of cell-free fetal DNA (cff-DNA) from maternal plasma using massively parallel sequencing enable the noninvasive detection of feto-placental chromosome aneuploidy; this technique has been widely used in clinics worldwide. Noninvasive prenatal tests (NIPT) based on cff-DNA have achieved very high accuracy; however, they suffer from maternal copy-number variations (CNV) that may cause false positives and false negatives. In this study, we developed an algorithm to exclude the effect of maternal CNV and refined the Z-score that is used to determine fetal aneuploidy. The simulation results showed that the algorithm is robust against variations of fetal concentration and maternal CNV size. We also introduced a method based on the discrepancy between feto-placental concentrations to help reduce the false-positive ratio. A total of 6615 pregnant women were enrolled in a prospective study to validate the accuracy of our method. All 106 fetuses with T21, 20 with T18, and three with T13 were tested using our method, with sensitivity of 100% and specificity of 99.97%. In the results, two cases with maternal duplications in chromosome 21, which were falsely predicted as T21 by the previous NIPT method, were correctly classified as normal by our algorithm, which demonstrated the effectiveness of our approach.

Statistical Approach to Decreasing the Error Rate of Noninvasive Prenatal Aneuploid Detection caused by Maternal Copy Number Variation